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DATA ASSIMILATION activities @SHMU

DATA ASSIMILATION activities @SHMU. M. Derkova , M. Bellus , M. Nestiak. ALADIN/SHMU: model characteristics. ALADIN/SHMU DA: methods (1). upper air spectral blending by DFI (surface fields copied from ARPEGE analysis) operational since 19/09/2007 surface

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DATA ASSIMILATION activities @SHMU

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  1. DATA ASSIMILATION activities @SHMU M. Derkova, M. Bellus, M. Nestiak

  2. ALADIN/SHMU: model characteristics

  3. ALADIN/SHMU DA: methods (1) upper air • spectral blending by DFI (surface fields copied from ARPEGE analysis) • operational since 19/09/2007 surface • data assimilation using CANARI (NEW !) • standard setting, no special tuning • operational since 03/04/2012 (difficult mental step)

  4. ALADIN/SHMU DA: methods (2) Data assimilation scheme: 6h frequency based on long cut-off observations and ARPEGE long cut-off LBC Production 4x/day based on short cut-off observations and short cut-off ARPEGE LBC

  5. ALADIN/SHMU DA: methods (3) get_oplace_long canari_assim blend_assim get_oplace_short canari_prod blend_prod

  6. ALADIN/SHMU DA: methods (4)DA step BLENDING ANALYSISBLEND GUESS ANALYSISSST ANALYSISSURF 6h FORECAST copy of SST CANARI BLENDING (no initialization) NEW GUESS

  7. ALADIN/SHMU DA: data (1) • data assimilated: SYNOP 2m temperature and 2m relative humidity • data sources: OPLACE + local database • SST copied from ARPEGE analysis • data processing: upgraded obsoul_merge script solves problem of corrupted OPLACE files

  8. OK PB!

  9. ALADIN/SHMU DA: data (3) New obsoul_merge script offers full control of observations: it reads the records and their headers one-by-one and checks many things. Duplicated records, records with wrong date or wrong observation type are excluded, lat/lon discrepancy of duplicated records is checked and so on. courtesy of M. Bellus, available upon request

  10. ALADIN/SHMU DA: data (4)listing with detailed debug info MERGING OBSOULS: => READING FILE (0): /data/nwp/products/oplace_long/2012-03-03/obsoul_1_xxxxxx_xx_2012030306 NT(orig): 06 NT(conv): 060000 => READING FILE (1): /data/nwp/products/oplace_long/2012-03-03/obsoul_5_xxxxxx_xx_2012030306 NT(orig): 06 NT(conv): 060000 => READING FILE (2): /data/nwp/products/obsoul/2012-03-03/obsoul_1_xxxxxx_xx_2012030306 NT(orig): 6 NT(conv): 060000 DATA PROCESSING: record number: 1 total data: 42 station ID: 13704 record number: 2 total data: 37 station ID: HU12805 record number: 3 total data: 42 station ID: 12812 ... ... record number: 3090 total data: 732 station ID: 01415 (!) 01415=> has wrong observation date/time ... record number: 3205 total data: 37 station ID: 17601 (!) 17601 => duplicated observation ... record number: 4583 total data: 32 station ID: 02095 (!) 02095 => has wrong lat/lon (saved:0.67/0.23 record:0.56/0.16) (file:20120303-060000 record:-533133308--5330800)

  11. ALADIN/SHMU DA: data (5)listing final info MERGING OBSOULS: => READING FILE (0): /data/nwp/products/oplace_long/2012-03-03/obsoul_1_xxxxxx_xx_2012030306 => READING FILE (1): /data/nwp/products/oplace_long/2012-03-03/obsoul_5_xxxxxx_xx_2012030306 => READING FILE (2): /data/nwp/products/obsoul/2012-03-03/obsoul_1_xxxxxx_xx_2012030306 => TOTAL RECORDS WRITTEN: 5349 (!) Number of skipped records due to inconsistent date/time: 104 (!) Number of skipped records due to inconsistent lat/lon: 82 (!) Number of skipped records due to duplicity: 2389 => FINISHED IN: 1 secs

  12. ALADIN/SHMU DA: validation (1) • 6months of e-suite (01/08/2011-30/01/2012) • reference = operational forecast (DFIblending) • veral • point verification • special diagnostics OPER CANARI 2mT analysis, 00UTC

  13. ALADIN/SHMUDA: validation (2) BIAS (left) and STDEV (right) of 2m temperature of the guess (blue) and of the CANARI analysis (red) computed over whole domain for few randomly selected days.

  14. CANARI ALADIN/SHMU DA: validation (3)“basic school” example 2mT analysis scores: top: over SK (OK), bottom: over whole domain (pb!) OPER

  15. ALADIN/SHMU DA: validation (4) What happens if SST is not correctly treated? Diff between CANARI analysis and ARPEGE(?) analysis with SST cycled (left) and copied (right)

  16. ALADIN/SHMU DA: validation (5) 2mT analysis scores over whole domain after correction OPER CANARI cycled SST CANARI copied SST

  17. ALADIN/SHMU DA: validation (6) Generally there was positive impact found on the analysis and subsequent forecasts; on the surface and also in lower levels; namely for temperature and humidity. The impact is more pronounced in summer period. Worsening of the daytime scores (in the summer): a problem in the forecasts for 12 and 18h day time, for any starting analysis time and any forecast length. A cold temperature BIAS (winter).

  18. CANARI OPER ALADIN/SHMUDA: validation (7) 2mT analysis 00UTC CANARI CANARI CANARI 2mT analysis 12UTC OPER OPER OPER OPER OPER

  19. CANARI CANARI OPER OPER ALADIN/SHMU DA: validation (8) 2mT +72h forecast 1000hPa T +12h forecast

  20. CANARI OPER ALADIN/SHMU DA: validation (9) 2mT +24h forecast from 12UTC 2mT +36h forecast from 00UTC

  21. ALADIN/SHMU DA: validation (10) 2mRH RMSE +24h forecast from 12UTC 2mRH RMSE +36h forecast from 00UTC OPER CANARI

  22. ALADIN/SHMU DA: validation (11) OPER CANARI

  23. ALADIN/SHMU DA: validation (12)2mT RMSE diurnal cycle (summer?) pb 00UTC CANARI OPER 12UTC

  24. ALADIN/SHMU DA: validation (13) difference of surface soil wetness in analyses between operational and parallel run

  25. ALADIN/SHMU DA: validation (14)cold 2mT BIAS (winter?) pb negative temperature BIAS in general for whole integration period near surface the temperature BIAS is negative mainly in winter season, but the fact, that it is generally worse for forecasts based on CANARI analyses comes from the warmer part of the testing period OPER CANARI 01/08/2011-30/01/2012 01/08/2011-31/10/2011 1/11/2011-30/01/2012

  26. RADAR assim in AROME/HU (1) Technical development for 3D-VAR assimilation of radial Doppler winds (using 3 HU radars). Preliminary results - analysis increments of U wind component for 3 model levels are shown.

  27. RADAR assim in AROME/HU (2) EXP0426 → 1117 c32160c13ae8730c2746b97b30b350ab BUD_20110426_0000.bufr

  28. RADAR assim in AROME/HU (3) EXP0426 → 1123_BU1117 C32160c13ae8730c2746b97b30b350ab BUD_20110426_0000.bufr (12843) 0a50b249103e46d11ae77022081e7bd2 NAP_20110426_0000.bufr (12892) 7044d9c633ced3c72943c8ccb43a6d98 POG_20110426_0000.bufr (12921)

  29. ALADIN/SHMU DA: plans • Solve 2m T forecast problems • Increase the horizontal/vertical resolution • Test coupling with ECMWF (MF new schedule) • 3DVAR/ALADIN installation – check basic impact • (optionally) 3VAR/AROME installation – to continue with radar DA

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